According to multiple surveys on oil and gas digital trends, analytics is a top priority for two-thirds of upstream oil and gas professionals when it comes to transforming their companies.
The oil and gas industry generates a wealth of data, from new geophones and logging tools to sensors, providing access to massive and diverse datasets. By leveraging analytics, companies can gain valuable insights into their operations, answer questions about past events, predict future outcomes, and determine appropriate next steps.
However, it’s essential to remember that analytics are only as good as the data they are based on. Therefore, the industry must prioritise data quality to ensure accurate and valuable insights. Furthermore, data management and security practices are changing rapidly as data becomes fully distributed and entirely situated in the cloud today.
Although the cloud has allowed businesses to continue operating seamlessly during and after the pandemic, the transition to distributed data that is no longer on-premises has presented a new IT challenge for organisations.
There needs to be more than the traditional hub-and-spoke security model for securing data in the cloud. Every organisation, whether in oil and gas or other sectors, should be thinking about implementing modern data loss prevention (DLP) practices.
Modern DLP tools make extensive use of machine learning (ML) algorithms, and the benefits of using these algorithms to improve DLP solutions are numerous.
Here are four ways that AI and machine learning can improve data loss prevention:
- Identifying sensitive and high-risk data: Machine learning can be instrumental in identifying and classifying the sensitive and high-risk data resources an organisation needs to protect. The cloud has complicated the process of categorising and classifying data elements, and manual processes cannot keep up.
- Automating the enforcement of a data handling policy: ML algorithms can streamline the enforcement of a data handling policy. Learning from prior incidents enables DLP tools to take proactive measures to protect data.
- Uncovering patterns of unauthorised data usage: Data is everywhere today, from employees’ laptops to the cloud. A DLP solution driven by ML can discern behaviour patterns to detect attempted unauthorised access.
- Offering more effective employee training: One of the features of modern DLP tools is their ability to provide employee training and education to promote a better understanding of the company’s data handling policy.
AI and machine learning are crucial for modern DLP solutions. By automating the identification and classification of sensitive data, enforcing data handling policies, detecting unauthorised access, and providing effective employee training, AI can significantly enhance organisations’ security practices in the cloud era.
It’s also important for organisations to consider implementing these modern DLP tools as distributed data and shadow IT continue to pose significant threats to data security.
Embracing modern DLP tools is essential to ensure data security and compliance
To explore the latest trends and best practices in the oil and gas industry, including an informative presentation on AI-Based Next Generation Intelligent DLP Systems, we are organising the Digital Twins for Oil & Gas Conference and Expo, powered by Oil & Gas Middle East and Construction Week Middle East.
The event will take place on May 31, 2023, at the Le Meridien Al Khobar Hotel in Saudi Arabia.
The opening keynote session titled “Digital Twins the Game Changer: Power of Predictive Digital Twins in Oil & Gas for a Sustainable Future” will kick off the event, showcasing the potential of digital twins in the industry.
The conference aims to provide insights into the potential of digital twins in the industry, with topics ranging from accelerating the hydrogen economy using digital twins to evaluating the need for a technology-enabled workforce to deliver projects successfully and the role of digital twins in clean energy.
Visit the conference website for more details to register for the event.
AI and machine learning can potentially revolutionise data loss prevention and security practices in the cloud era. As more oil and gas organisations shift to the cloud and distributed data environments, embracing these modern DLP tools is essential to ensure data security and compliance.
